1. Field of Invention
The present invention relates to image acquisition and display, and more particularly to a spectral sampling arrangement for a color filter array.
2. Discussion of Related Art
In digital imaging applications, data are typically obtained via a spatial subsampling procedure implemented as a color filter array (CFA), a physical construction whereby each pixel location measures only a single color. The most well known of these schemes involve the canonical primary colors of light: red, green, and blue. In particular, the Bayer pattern CFA attempts to complement humans' spatial color sensitivity via a quincunx sampling of the green component that is twice as dense as that of red and blue. Specifically, let n=(n0,n1) index pixel locations and definex(n)=(r(n),g(n),b(n))  (1)to be the corresponding color triple. Then the Bayer pattern CFA image, yBAYER(n), is given by:yBAYER(n)=rs(n)+gs(n)+bs(n),  (2)where
                                          r            s                    ⁡                      (            n            )                          =                  {                                                                                                                r                      ⁡                                              (                        n                        )                                                                                                                                                if                        ⁢                                                                                                  ⁢                                                  n                          0                                                                    ,                                                                        n                          1                                                ⁢                                                                                                  ⁢                        even                                                                                                                                  0                                                        otherwise                                                              ⁢                                                          ⁢                                                g                  s                                ⁡                                  (                  n                  )                                                      =                          {                                                                                                                                            g                          ⁡                                                      (                            n                            )                                                                                                                                                                            if                            ⁢                                                                                                                  ⁢                                                          n                              0                                                                                +                                                                                    n                              1                                                        ⁢                                                                                                                  ⁢                            odd                                                                                                                                                              0                                                                    otherwise                                                                              ⁢                                                                          ⁢                                                            b                      s                                        ⁡                                          (                      n                      )                                                                      =                                  {                                                                                                              b                          ⁡                                                      (                            n                            )                                                                                                                                                                            if                            ⁢                                                                                                                  ⁢                                                          n                              0                                                                                ,                                                                                    n                              1                                                        ⁢                                                                                                                  ⁢                            odd                                                                                                                                                              0                                                                                              otherwise                          .                                                                                                                                                                            (        3        )            
Some existing alternatives to the Bayer pattern include Fuji's octagonal sampling, Sony's four color sampling, Polaroid's striped sampling, CMY sampling, hexagonal sampling, and irregular patterns. The Bayer pattern is illustrated in FIG. 1A, four color sampling is illustrated in FIG. 1B, striped sampling is illustrated in FIG. 1C, and hexagonal sampling is illustrated in FIG. 1D.
The terms “Demosaicing” or “demosaicking” refer to the inverse problem of reconstructing a spatially undersampled vector field whose components correspond to particular colors. Use of the Bayer sampling pattern is ubiquitous in today's still and video digital cameras; it can be fairly said to dominate the market. Consequently, much attention has been given to the problem of demosaicing color images acquired under the Bayer pattern sampling scheme.
While a number of methods have been proposed for reconstruction of subsampled data patterns, it is well known that the optimal solution (in the sense of minimal norm) to this ill-posed inverse problem, corresponding to bandlimited interpolation of each spatially subsampled color channel separately, produces perceptually significant artifacts. The perceptual artifacts produced using demosaicing algorithms on sub-sampled data obtained using a Bayer-pattern is caused both by the spatial undersampling inherent in the Bayer pattern and the observation that values of the color triple exhibit significant correlation, particularly at high spatial frequencies: such content often signifies the presence of edges, whereas low-frequency information contributes to distinctly perceived color content. As such, most demosaicing algorithms described in the literature attempt to make use (either implicitly or explicitly) of this correlation structure in the spatial frequency domain.
Most work in this area focuses on the interplay between the acquisitions stages and subsequent digital processing. Assuming a full-color image (i.e., a full set of color triples), and consequently, a key reconstruction task of demosaicing is first necessary.
A color filter array represents one of the first steps in the image acquisition pipeline and by considering the entire pipeline, analysis is provided on existing designs. For example, Fourier analysis may be applied, permitting a view of demosaicking as a process of “demulitplexing.” Fourier analysis may also be applied to reconstruction based on chrominance/luminance decomposition. This analysis has led to surprising results.